



'''simple docstring'''





from ...configuration_utils import PretrainedConfig


class 					snake_case			(lowerCamelCase__ ):
       lowerCAmelCase__	:Optional[int]     =       "bert-generation"



       def __init__(					self  ,UpperCAmelCase_=50_358  ,UpperCAmelCase_=1_024  ,UpperCAmelCase_=24  ,UpperCAmelCase_=16  ,UpperCAmelCase_=4_096  ,UpperCAmelCase_="gelu"  ,UpperCAmelCase_=0.1  ,UpperCAmelCase_=0.1  ,UpperCAmelCase_=512  ,UpperCAmelCase_=0.02  ,UpperCAmelCase_=1E-1_2  ,UpperCAmelCase_=0  ,UpperCAmelCase_=2  ,UpperCAmelCase_=1  ,UpperCAmelCase_="absolute"  ,UpperCAmelCase_=True  ,**UpperCAmelCase_  ,)	->				Tuple:
           super().__init__(pad_token_id=__snake_case  ,bos_token_id=__snake_case  ,eos_token_id=__snake_case  ,**__snake_case   )

           lowercase__									=    vocab_size
           lowercase__									=    hidden_size
           lowercase__									=    num_hidden_layers
           lowercase__									=    num_attention_heads
           lowercase__									=    hidden_act
           lowercase__									=    intermediate_size
           lowercase__									=    hidden_dropout_prob
           lowercase__									=    attention_probs_dropout_prob
           lowercase__									=    max_position_embeddings
           lowercase__									=    initializer_range
           lowercase__									=    layer_norm_eps
           lowercase__									=    position_embedding_type
           lowercase__									=    use_cache









'''simple docstring'''






# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import re

from ..models.auto import AutoProcessor
from ..models.vision_encoder_decoder import VisionEncoderDecoderModel
from ..utils import is_vision_available
from .base import PipelineTool


if is_vision_available():
     from PIL import Image

class 				a__(   lowerCamelCase__      ):
    lowercase__					=       """naver-clova-ix/donut-base-finetuned-docvqa"""
    lowercase__					=       (
        """This is a tool that answers a question about an document (pdf). It takes an input named `document` which """
        """should be the document containing the information, as well as a `question` that is the question about the """
        """document. It returns a text that contains the answer to the question."""
    )
    lowercase__					=       """document_qa"""
    lowercase__					=       AutoProcessor
    lowercase__					=       VisionEncoderDecoderModel

    lowercase__					=       ["""image""", """text"""]
    lowercase__					=       ["""text"""]







    def __init__( self					:    str		,     *__snake_case					:    Any		,     **__snake_case					:    List[Any]      ):
      if not is_vision_available():
        raise ValueError('Pillow must be installed to use the DocumentQuestionAnsweringTool.'      )

      super().__init__(*__snake_case		,     **__snake_case      )







    def      lowercase_			( self					:    Union[str, Any]		,     __snake_case					:    "Image"		,     __snake_case					:    str      ):
      a		:   Union[str, Any]	  =	'<s_docvqa><s_question>{user_input}</s_question><s_answer>'
      a		:   Any	  =	task_prompt.replace('{user_input}'		,     __snake_case      )
      a		:   Dict	  =	self.pre_processor.tokenizer(
          __snake_case		,     add_special_tokens=__snake_case		,     return_tensors='pt'      ).input_ids
      a		:   Tuple	  =	self.pre_processor(__snake_case		,     return_tensors='pt'      ).pixel_values

      return {"decoder_input_ids": decoder_input_ids, "pixel_values": pixel_values}







    def      lowercase_			( self					:    Any		,     __snake_case					:    int      ):
      return self.model.generate(
          inputs['pixel_values'].to(self.device      )		,     decoder_input_ids=inputs['decoder_input_ids'].to(self.device      )		,     max_length=self.model.decoder.config.max_position_embeddings		,     early_stopping=__snake_case		,     pad_token_id=self.pre_processor.tokenizer.pad_token_id		,     eos_token_id=self.pre_processor.tokenizer.eos_token_id		,     use_cache=__snake_case		,     num_beams=1		,     bad_words_ids=[[self.pre_processor.tokenizer.unk_token_id]]		,     return_dict_in_generate=__snake_case		,     ).sequences







    def      lowercase_			( self					:    List[str]		,     __snake_case					:    Tuple      ):
      a		:   str	  =	self.pre_processor.batch_decode(__snake_case      )[0]
      a		:   str	  =	sequence.replace(self.pre_processor.tokenizer.eos_token		,     ''      )
      a		:   Union[str, Any]	  =	sequence.replace(self.pre_processor.tokenizer.pad_token		,     ''      )
      a		:   List[str]	  =	re.sub(r'<.*?>'		,     ''		,     __snake_case		,     count=1      ).strip()  # remove first task start token
      a		:   Dict	  =	self.pre_processor.tokenajson(__snake_case      )

      return sequence["answer"]